PT - JOURNAL ARTICLE
AU - Grabitz, Peter
AU - Lazebnik, Yuri
AU - Nicholson, Josh
AU - Rife, Sean
TI - Science with no fiction: measuring the veracity of scientific reports by citation analysis
AID - 10.1101/172940
DP - 2017 Jan 01
TA - bioRxiv
PG - 172940
4099 - http://biorxiv.org/content/early/2017/08/09/172940.short
4100 - http://biorxiv.org/content/early/2017/08/09/172940.full
AB - The current crisis of veracity in biomedical research is enabled by the lack of publicly accessible information on whether the reported scientific claims are valid. One approach to solve this problem is to replicate previous studies by specialized reproducibility centers. However, this approach is costly or unaffordable and raises a number of yet to be resolved concerns that question its effectiveness and validity. We propose to use an approach that yields a simple numerical measure of veracity, the R-factor, by summarizing the outcomes of already published studies that have attempted to test a claim. The R-factor of an investigator, a journal, or an institution would be the average of the R-factors of the claims they reported. We illustrate this approach using three studies recently tested by a replication initiative, compare the results, and discuss how using the R-factor can help improve the veracity of scientific research.